News
Epistemic Diversity and Knowledge Collapse in Large Language Models
arXiv:2510.04226v4 Announce Type: replace Abstract: Large language models (LLMs) tend to generate lexically, semantically, and...
EPFL Researchers Unveil FG2 at CVPR: A New AI Model That Slashes Localization Errors by 28% for Autonomous Vehicles in GPS-Denied Environments
Navigating the dense urban canyons of cities like San Francisco or New York can be...
EPFL Researchers Introduce MEMOIR: A Scalable Framework for Lifelong Model Editing in LLMs
The Challenge of Updating LLM Knowledge LLMs have shown outstanding performance for various tasks through...
Entropy2Vec: Crosslingual Language Modeling Entropy as End-to-End Learnable Language Representations
arXiv:2509.05060v1 Announce Type: new Abstract: We introduce Entropy2Vec, a novel framework for deriving cross-lingual language...
Entropy-Guided Reasoning Compression
arXiv:2511.14258v1 Announce Type: new Abstract: Large reasoning models have demonstrated remarkable performance on complex reasoning...
Entrepreneurs in Nairobi make the case for going solar
__________________________THE PLACENairobi, Kenya Most of Kenya’s power grid runs on renewables. But with 25% of...
Enterprise alert: PostgreSQL just became the database you can’t ignore for AI applications
Analysts provide insight on what the latest acquisition of a PostgreSQL database vendor means for...
Enterprise AI’s real risk isn’t autonomous agents. It’s the complexity between them.
Presented by Gravitee Agent complexity is the insidious shadow lurking inside enterprises right now that...
Enterprise AI Without GPU Burn: Salesforce’s xGen-small Optimizes for Context, Cost, and Privacy
Language processing in enterprise environments faces critical challenges as business workflows increasingly depend on synthesising...
Enigmata’s Multi-Stage and Mix-Training Reinforcement Learning Recipe Drives Breakthrough Performance in LLM Puzzle Reasoning
Large Reasoning Models (LRMs), trained from LLMs using reinforcement learning (RL), demonstrated great performance in...
Enhancing Test-Time Scaling of Large Language Models with Hierarchical Retrieval-Augmented MCTS
arXiv:2507.05557v1 Announce Type: new Abstract: Test-time scaling has emerged as a promising paradigm in language...
Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach
arXiv:2508.21206v1 Announce Type: new Abstract: Autoregressive language models are vulnerable to orthographic attacks, where input...
